DPL Reading List – November 2, 2018

Your Team Doesn’t Need a Data Scientist for Simple Analytics – “Data analytics is a powerful and promising source of competitive advantage. To enable such a strategy in the face of a difficult shortfall of the requisite talent in the marketplace, one must fall back on developing existing employees through cross-training and cross-pollination of team members and experts. To embark on this strategy, we shouldn’t wait for that singular blazing torch-bearer to light the darkness. It is more pragmatic to help the rank-and-file member to become a candle, and from the collective light, illuminate the darkness.”

A groundbreaking study reveals how we want machines to treat us – ““Never in the history of humanity have we allowed a machine to autonomously decide who should live and who should die, in a fraction of a second, without real-time supervision,” the researchers write. “We are going to cross that bridge any time now, and it will not happen in a distant theater of military operations; it will happen in that most mundane aspect of our lives, everyday transportation. Before we allow our cars to make ethical decisions, we need to have a global conversation to express our preferences to the companies that will design moral algorithms, and to the policymakers that will regulate them.””

Building a Time Machine for Radio – “It’s the large size of the recordings that poses the biggest obstacle to Witherspoon’s plan to gather more recordings and make them publicly accessible online. One way the team is tackling the problem is by focusing on preserving recordings associated with newsworthy events. For example, “when the North Korea talks were happening, we were doing AM broadcast-band recordings. But since the news didn’t change a lot during the day, we chose to preserve only a 2-hour segment.” Witherspoon estimates that they currently have about 150 terabytes of recordings “curated to the point that it’s worth uploading them.””

The future of passwords? Your brain – “It’s easy enough to authenticate a person’s identity another way, and have them set a new password by looking at three new images–maybe this time with a photo of a dog, a drawing of George Washington and a Gandhi quote. Because they’re different images from the initial password, the brainwave patterns would be different too. Our research has found that the new brain password would be very hard for attackers to figure out, even if they tried to use the old brainwave readings as an aid.”

A.I. Is Helping Scientists Predict When and Where the Next Big Earthquake Will Be – “Scientists say seismic data is remarkably similar to the audio data that companies like Google and Amazon use in training neural networks to recognize spoken commands on coffee-table digital assistants like Alexa. When studying earthquakes, it is the computer looking for patterns in mountains of data rather than relying on the weary eyes of a scientist.”

Photography’s Future is Computational – “The ability to concentrate on the artistic aspects of photography rather than the technical details will open doors for many while the inclusion of these technologies in cheaper camera systems will foster wide-spread adoption in the form of smartphones and other small camera systems. Professionals can look forward to insanely awesome post-processing tools in the near future while the allure of a major camera system with the features I have described is something that will likely come to fruition over the span of several years.”

Apple News’s Radical Approach: Humans Over Machines – “Ms. Kern criticized the argument that algorithms are the sole way to avoid prejudice because bias can be baked into the algorithm’s code, such as whether it labels news organizations liberal or conservative. She argued that humans — with all their biases — are the only way to avoid bias. “We’re so much more subtly following the news cycle and what’s important,” she said. “That’s really the only legitimate way to do it at this point.””